In order to preserve data saved in a hard disk drive (HDD), it is important to grasp the health status of the HDD. Analyzing operating history data on failure HDDs can construct a failure symptom model for detecting future failure occurrence from operating data. Using the failure symptom model, a probability of failure occurrence, for example, within a predetermined period is calculated. When the probability is equal to or greater than a threshold, the presence of a failure symptom can be determined.
In this case, change in product generation sometimes leads to change in behavior of the HDD and the failure symptom model constructed from past operating data does not possibly achieve accuracy as expected. In order to investigate the accuracy of the model with respect to an HDD in a new generation, the operating history data on the failure HDDs is needed. Accumulation of the data takes time. Assuming that the model is applied to failure symptom detection of the HDD in the new generation with the investigation of the accuracy being insufficient, low accuracy of the model causes a problem of frequent occurrence of overlooking and erroneous warning. The overlooking means that a failure occurs within a predetermined period in spite of a prediction result indicating the absence of a failure symptom. The misdetection means that a failure does not occur within a predetermined period in spite of the presence of a failure symptom.